Robust sensing of dvb-t/h transmissions

ABSTRACT

A method and system is provided for detecting the presence of a DVB (digital video broadcasting) transmission. The method includes receiving an RF (radio frequency) signal in a selected channel ( 1101 ); creating signal samples from the received RF signal ( 1102 ); creating averaged samples from the signal samples, each averaged sample being an average of a predetermined number of signal samples that are separated by a minimum pilot pattern repetition period from one to the next signal sample ( 1103 ); correlating the averaged samples with a reference sequence ( 1104 ); and comparing a correlation result with a threshold correlation value ( 1105 ).

This application claims the benefit of U.S. Provisional Application No.61/178,231 filed on May 14, 2009.

The invention generally relates to devices in a Cognitive Radio (CR)network, and more particularly, to a method and system which sensesdigital video broadcasting (DVB) transmissions.

New spectrum policies being adopted by the regulatory bodies envisionthe operation of unlicensed secondary devices in the frequency bandsdesignated for licensed operation. The secondary devices can operateonly when that band is vacant or not being used by a primary device.This implies that the secondary devices have to vacate the band when aprimary device starts transmission in order to minimize the amount ofinterference the secondary devices would cause to the primary devices.The secondary devices are also referred to as Cognitive Radios (CR) dueto their ability to sense the environment and adapt accordingly. The UHF(ultra high frequency) band allocated for television broadcasting is anideal candidate for allowing the operation of CR devices.

In the US, in order to avoid interference to or from broadcasts fromneighboring markets and/or transmissions, only some of the TV bands canbe used in any given geographical location. As a result, the remainingTV bands are largely unused and therefore can be utilized for otherpurposes (such as in-home networking, etc). Other regulatory domainsalso have similar allocation of TV channels.

To avoid harmful interference to digital television (DTV) reception by,for example, CR devices, regulatory bodies have stipulated reliabledetection of DTV signals at signal strengths as low as −114 dBm. Thusthe CR devices should sense the channel for primary transmissions beforethey can use that particular channel. This requirement mandates that theCR devices implement robust sensing algorithms to detect the presence ofDTV (DVB-T/H) (Digital Video Broadcasting—Terrestrial/Handheld) signals.

However, unlike the 8-VSB (8-level vestigial sideband) ATSC (AdvancedTelevision Systems Committee) signal which has a single pilot at a knownlocation in the frequency domain, a DVB-T signal has a number oflower-power pilots distributed in the frequency domain. Hence theapproach of filtering in the frequency domain in order to detect thepilots is not feasible for DVB-T. Instead, a better approach would be tocorrelate in the time domain with a known time domain signalrepresenting the frequency domain pilots.

Existing sensing algorithms for the detection of DVB-T and DVB-H signalswork well only with a sub-set of transmission modes. According toembodiments herein, a sensing algorithm improves the detectionperformance and performs equally well for all the transmission modes.

Most OFDM (orthogonal frequency division multiplexing) signals, such asthose used to transmit digital television using DVB-T, have pilots inthe frequency domain for channel estimation and synchronization. Thereare two kinds of pilot signals embedded into the data stream: (1) fixedpilots, whose values and locations are fixed and (2) variable pilotswhose values are fixed but the locations change from symbol to symbol,sometimes repeating in a known pattern. Both kinds can be used forsensing, depending on the degree of desired complexity. The fundamentalapproach taken here is to view these pilots in the time domain as acontinuous known sequence that is embedded into the data sequence and tocorrelate the received signal with this known sequence. Since DVB-T hasa number of different FFT (Fast Fourier Transform) sizes and cyclicprefixes, a different reference signal is generated for each mode andcorrelated against each to determine the type of signal present.

In one example embodiment of the invention, a method is provided fordetecting the presence of a DVB (digital video broadcasting)transmission. The method includes receiving an RF (radio frequency)signal in a selected channel; creating signal samples from the receivedsignal; creating averaged samples from the signal samples, each averagedsample is an average of a predetermined number of signal samples thatare separated by a minimum pilot pattern repetition period from one tothe next signal sample; correlating the averaged samples with areference sequence; and comparing a correlation result with a thresholdcorrelation value.

In another example embodiment of the invention, a system is provided fordetecting the presence of a DVB transmission. The system includes an RFfront-end module for receiving an RF signal; a sampling module forcreating signal samples from the received RF signal; a buffer forholding the signal samples; an accumulating/averaging module forcreating averaged samples from the signal samples, each averaged sampleis an average of a predetermined number of signal samples that areseparated by a minimum pilot pattern repetition period from one to thenext signal sample; a memory module for storing a reference sequence; acorrelator for correlating the averaged samples with the referencesample; and a threshold detection module for comparing a correlationresult with a threshold correlation value.

The subject matter that is regarded as the invention is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The foregoing and other features and advantages ofthe invention will be apparent from the following detailed descriptiontaken in conjunction with the accompanying drawings.

FIG. 1 illustrates an OFDM symbol with cyclic prefix (CP).

FIG. 2 illustrates the location of scattered pilot sub-carriers in DVB-TOFDM symbols.

FIG. 3 illustrates the correlation on CP for 2K, 1/32 mode with SNRs of5 dB and −5 dB.

FIG. 4 illustrates the correlation on pilots for 2K, 1/32 mode with SNRsof −5 dB and −10 dB.

FIG. 5 illustrates a block diagram of a DVB-T detector using datasmoothing in one embodiment of the invention.

FIG. 6 illustrates a block diagram of a DVB-T detector using datasmoothing in another embodiment of the invention.

FIG. 7 illustrates a comparison of correlation plot without (top) andwith (bottom) data smoothing for 2K, 1/32 mode with an SNR of −15 dB andL=8.

FIG. 8 illustrates the performance of the improved detector in an AWGNand Rayleigh faded channel for 2K, 1/32 mode.

FIG. 9 illustrates a comparison of the performance of a standard(without data smoothing) and the robust (with data smoothing) in an AWGNand Rayleigh faded channel for 2K, 1/32 mode.

FIG. 10 illustrates the performance of the DVB-T detector using thesimplified cross-correlator.

FIG. 11 illustrates a process for detecting the presence of a DVBsignal.

It is important to note that the embodiments disclosed by the inventionare only examples of the many advantageous uses of the innovativeteachings herein. In general, statements made in the specification ofthe present application do not necessarily limit any of the variousclaimed inventions. Moreover, some statements may apply to someinventive features but not to others. In general, unless otherwiseindicated, singular elements may be in plural and vice versa with noloss of generality. In the drawings, like numerals refer to like partsthrough several views.

Brief Overview of DVB-T Transmission Specification

The terrestrial Digital Video Broadcasting (DVB-T) has been standardizedby the European Telecommunications Standards Union (ETSI) for theterrestrial broadcasting of digital TV. The DVB-T standard uses anorthogonal frequency division multiplexing (OFDM) modulation scheme andprovides options to adapt the coding and modulation parameters accordingto broadcaster's requirements. The DVB-T specification provides twomodes of operations: namely, the ‘2K mode’ and the ‘8K mode’. Inaddition, the DVB-H enhancement provides the ‘4K mode’. The modes aredefined based on the FFT (Fast Fourier Transform) size used to generatethe transmitted signals. Some of the parameters for each of these modesare listed in Table 1.

TABLE 1 DVB-T Parameters for 8K and 2K mode Parameter 8K mode 2K modeNumber of carriers K 6817 1705 Value of carrier number K_(min) 0 0 Valueof carrier number K_(max) 6816 1704 Duration T_(U) 896 μs 224 μs CarrierSpacing 1/T_(U) 1116 Hz 4464 Hz Spacing between carriers K_(min) and7.61 MHz 7.61 MHz K_(max) (K − 1)/T_(U)

The DVB-T transmitted signal is organized in frames. Each frame consistsof 68 OFDM symbols and four such frames make up a super-frame. As shownin FIG. 1, an OFDM symbol 100 consists of two parts: a useful symbolperiod 102 and a guard interval 101. A portion of the useful symbol istransmitted in guard interval 101 (referred to as cyclic prefix (CP)),and this feature is used to minimize the inter-symbol interference. TheDVB-T specification provides a choice of ¼, ⅛, 1/16 or 1/32 of thesymbol period for the guard interval.

In addition to the CP, the DVB-T standard provides the followingreference signals to assist in the synchronization, demodulation anddecoding of the signal.

-   -   Continual pilots—These reference signals are placed at fixed        sub-carriers locations, and their location does not vary from        symbol to symbol. There are 45 continual pilots in the ‘2K mode’        and 177 continual pilots in the ‘8K mode’.    -   Scattered pilots—These reference signals 201 (FIG. 2) are        distributed evenly (every 12^(th) sub-carrier) in the OFDM        symbol. The location of these pilots is offset by three        sub-carriers on each OFDM symbol and as a result, the pilot        pattern repeats every four OFDM symbols in frame 200, as shown        FIG. 2. The scattered pilots are used to derive the channel        estimate assuming that the channel is quasi-static.    -   TPS pilots—These Transmission Parameter Signaling (TPS)        reference signals are used to carry the transmission parameters.        A fixed set of 17 sub-carriers for the ‘2K mode’ and 68        sub-carriers for the ‘8K mode’ has been designated as TPS pilot        sub-carriers. All the TPS pilot sub-carriers in an OFDM symbol        carry the same information.

The continual pilots and scattered pilots are transmitted at a higherpower level (˜2.5 dB) compared to the rest of the sub-carriers.

DVB-T Signal Detection Methods Energy Based Detection Schemes

Detecting the presence of signal energy in the channel of interest isusually very fast and provides a good indication of channel occupancy.This method however does not provide any information about the signalitself, and therefore it cannot distinguish between a primary signal anda secondary signal. In addition, the probability of detection variessignificantly with the thresholds. As a result, extreme care has to betaken while determining the threshold value to be used, especially whiledetecting signals with low signal to noise ratios (SNR).

Feature Based Detection Schemes

Feature based detection schemes rely on the unique features of theincumbent signals (such as training signals, pilot patterns, etc.) fordetection. As mentioned earlier, the DVB-T signal has some uniquefeatures in terms of the cyclic prefix, continual and scattered pilots,etc., which can be used in the detection process.

Time Domain Auto-Correlation

In time domain auto-correlation, the CP feature of the DVB-T signal isused to determine the presence or absence of the signal in the channel.The received signal is correlated with a delayed version of the signalas shown in the following equation:

$\begin{matrix}{{R_{{xx}\;}(n)} = {\sum\limits_{m = n}^{n + N_{GI} - 1}{{x(m)}x^{*}\; \left( {m + N_{FFT}} \right)}}} & (1)\end{matrix}$

Where x(m) is the sampled received signal in the time-domain andR_(xx)(n) is the auto-correlation of x(m). N_(FFT), N_(GI) and N_(SYM)represent the FFT, CP and OFDM symbol lengths respectively.

Since a portion of the useful OFDM symbol is repeated in CP, correlatingas above will give a peak that repeats periodically. The peak amplitudewith an optional combination with peak periodicity can be used to detectthe presence of DVB-T signals in the channel of interest.

-   -   Let R _(xx) the peak value of |R_(xx)(n)|² defined as

$\begin{matrix}{{\overset{\_}{R}}_{xx} = {\max\limits_{n}\left( {{R_{xx}\; (n)}}^{2} \right)}} & (2)\end{matrix}$

Then R _(xx) is compared against a pre-defined threshold, T_(xx) ^(CP),to determine the presence of the signal.

R _(xx)>T_(xx) ^(CP) signal present

otherwise signal absent  (3)

The threshold is determined based on the desired false alarmprobability.

The auto-correlation based detector performs very well for high SNRvalues. However, for moderate and low SNRs values (i.e., below 0 dB) theperformance may not be very reliable. In addition, the performancedepends significantly on the CP length. As a result, the detectorperforms well for the 8K mode with ¼ GI and very poorly for the 2K modewith 1/32 GI. The detector, however, is robust to frequency offsets.FIG. 3 shows the auto-correlation plots 301, 302 for the 2K, 1/32 modewith SNRs of 5 dB and −5 dB. It can be observed that for SNR=−5 dB, thecorrelation peaks are not clearly distinguishable and as a result thedetector's performance degrades (see plot 302).

Time Domain Cross-Correlation

In the time domain cross-correlation method, the continual and scatteredpilots in the DVB-T signal are used to detect the signal. As describedin the previous section, a sub-set of the carriers are designated aspilot sub-carriers. These carriers carry known information and thesecarriers are transmitted at higher power (by about 2.5 dB) compared tothe data carriers. The received signal can be correlated with areference sequence which is derived by taking an inverse Fouriertransform of a vector composed of only the pilot sub-carriers. Since theSP pattern repeats every four symbols, forming four such referencesignals s_(d) ^(P) (n) is shown below

$\begin{matrix}{{{s_{d}^{P}(n)} = {\sum\limits_{k \in \Psi_{P,d}}{C_{k,d}^{\frac{j\; 2\pi \; {kn}}{N_{FFT}}}}}},} & (4)\end{matrix}$

where s_(d) ^(P) (n) represents the time-domain sequence, d representsthe pilot pattern number and takes the values 1 to 4. Ψ_(P,d) representsthe set of pilot sub-carriers locations for pilot pattern number d. Theset of pilot sub-carriers could only be those corresponding to scatteredpilot locations or a combined set of scattered and continual pilotlocations. For example, for the case of SP, Ψ_(P,1)={0,12,24, . . . }.C_(k,d) represents the symbol for sub-carrier k and pattern number d.

Another reference sequence can also be generated by combining the abovefour reference sequences as shown below:

s _(comb) ^(P)(n)=s ₁ ^(P)(n)+s ₂ ^(P)(n−N _(FFT))+s ₃ ^(P)(n−2N_(FFT))+s ₄ ^(P)(n−3N _(FFT)),  (5)

where n=0 to (4 N_(FFT)−1).

The correlation output is given by the following equation:

$\begin{matrix}{{R_{{xp},d}(n)} = {\sum\limits_{m = 0}^{N_{FFT} - 1}{{x^{*}\left( {n + m} \right)}{s_{d}^{P}(m)}}}} & (6)\end{matrix}$

In ideal conditions, the correlator output R_(xp,d) (n) would have apeak magnitude that repeats every 4T_(SYM) samples.

A similar equation for the correlation output can be derived for thecase when s_(comb) ^(p) (n) is used as a reference sequence as shownbelow

$\begin{matrix}{{R_{{xp},{comb}}(n)} = {\sum\limits_{d = 1}^{4}{\sum\limits_{m = 0}^{N_{FFT} - 1}{{x^{*}\left( {n + {\left( {d - 1} \right)*N_{SYM}} + m} \right)}{s_{d}^{P}(m)}}}}} & (7)\end{matrix}$

In the rest of this section, R_(xp,1) (n) to derive detection metricswill be considered. The analysis can be extended to all the correlationoutputs derived previously.

Let R _(xp,1) represent the peak value of |R_(xp,1) (n)|² defined as

$\begin{matrix}{{\overset{\_}{R}}_{{xp},1} = {\max\limits_{n}\left( {{R_{{xp},1}(n)}}^{2} \right)}} & (8)\end{matrix}$

Then R _(xp,1) is compared against a pre-defined threshold, T_(xp) ^(P),to determine the presence of the signal.

R _(xp,1)>T_(xp) ^(P) signal present

otherwise signal absent  (9)

The cross-correlation based detector performs very well in differentchannel environments even for low SNR values. In addition, the detectorperformance is independent of transmission mode and therefore performsequally well for the 2K mode, as well as the 8K mode.

FIG. 4 shows the correlator output 401, 402 for the 2K, 1/32transmission mode for SNRs of −5 dB and −10 dB. s _(i) ^(P) (n) was usedas the reference sequence. It can be observed from the plots 401 and 402that the performance of the cross-correlation based detector is bettercompared to that of the auto-correlation based detector.

Method to Detect DVB-T Signals

Following are example embodiments describing advanced algorithms toimprove the detector's performance

Since the DVB-T deployments are static, it is assumed that the channelbandwidth and the transmission mode (FFT size and GI duration)information are available to the detector. In cases where transmissionmode information is not available, the detector can cycle through thedifferent transmission modes to sense for DVB-T signals. This wouldresult in increased detection time, but the detection performanceremains substantially the same.

Improved Detection by Data Smoothing (Reducing Noise Variance)

Referring to Equation (6), it can be observed that the correlationoutput contains a noise term (contributions from data sub-carriers andWGN). In one example embodiment of the invention, the variance of thenoise term can be reduced by averaging the received symbols. However,the detector does not know the symbol boundaries. Assuming that thetransmission mode and GI duration are known, then the minimum pilotpattern repetition period (PPRP) can be derived using the followingequation N_(PPRP)=N_(GI)*N_(SYM). Alternatively, the minimum PPRP can bederived using the equation N_(PPRP)=4*B*N_(SYM), where B is an integer.Using this fact, the received samples are averaged, as shown below

$\begin{matrix}{{{x_{L}(n)} = {\frac{1}{L}{\sum\limits_{l = 0}^{L - 1}{x\left( {n - {l*N_{PPRP}}} \right)}}}}{{n = 0},1,\ldots \mspace{14mu},{N_{PPRP} - 1},}} & (10)\end{matrix}$

where L is a design parameter and is dependent on the sensing time andthe desired performance.

The averaged samples x_(L)(n) are correlated with reference sequences asfollows:

$\begin{matrix}{{{R_{{xp},d}^{L}(n)} = {\sum\limits_{m = 0}^{N_{FFT} - 1}{{x_{L}^{*}\left( {n + m} \right)}{s_{d}^{P}(m)}}}}{{n = 0},1,\ldots \mspace{14mu},N_{PPRP}}} & (11)\end{matrix}$

Any range, equal to 4*N_(SYM) samples within [0, N_(PPRP)−1] can be usedto determine the maximum peak magnitude. Additional peak magnitudes canalso be derived and verified if the consistency of the peak location isused to improve the robustness of the detector.

Let R _(xp,1) ^(L) represent the peak value of |R^(L) _(xp,1)(n)|²defined as

$\begin{matrix}{{\overset{\_}{R}}_{{xp},1}^{L} = {\max\limits_{n}\left( {{R_{{xp},1}^{L}(n)}}^{2} \right)}} & (12)\end{matrix}$

Then R _(xp,1) ^(L) is compared against a pre-defined threshold, T_(xp)^(P,L), to determine the presence of the signal.

R _(xp,1) ^(L)>T_(xp) ^(P,L) signal present

otherwise signal absent  (13)

FIG. 5 shows a simplified block diagram of a DVB-T detector 500 usingdata smoothing. The RF front-end 501 down-shifts the RF signal to anintermediate frequency (IF). The IF signal is then down-shifted to DC(alternatively, the IF signal can be downshifted to DC in the digitaldomain, i.e. after ADC). The signal is then digitized by an analog todigital converter (ADC) 502. The sampled signal is then processedaccording to the methods described above, using the modules buffer 503,accumulate/average 505 and correlator 506. The buffer 503,accumulate/average 505 and correlator 506 modules operate based on aparticular transmission mode, and the detector can operate on differenttransmission modes. An alternate arrangement 600, as shown in FIG. 6, isthat the correlator 506 is placed before the buffer 503, so that thecorrelation is performed before the buffering, accumulating andaveraging. The signal ‘seq ID’ determines the reference sequence, whichis generated from pilots and is stored in memory 504, to be used forcorrelation. This signal is also used by the ‘Threshold Detection’module 507 to determine the thresholds to be used. The output of thecorrelator is compared against the selected threshold to determine thepresence/absence of a DVB-T signal.

FIG. 7 shows the effect of data smoothing on the correlation output. Thecorrelation outputs without data smoothing 701 and with data smoothing702 demonstrate that the peaks are distinctly visible when the data issmoothed as described earlier, and therefore the detector is able todetect the DVB-T signals even for SNRs below −15 dB.

The performance of the proposed algorithm was evaluated throughsimulations in AWGN and multi-path channel. The following simulationparameters were used:

-   -   Transmission mode—2K, 1/32    -   Number of runs for each SNR—1000,    -   Smoothing factor L—8 (˜60 ms sensing time)    -   Probability of false alarm (P_(FA))—<0.01    -   Channels: AWGN or Rayleigh faded

FIG. 8 shows the probability of detection (P_(d)) vs. SNR curves for theproposed detector in the AWGN channel 801 and Rayleigh channel 802. FIG.9 shows the P_(d) vs. SNR curves for the example embodiment detector(AWGN with averaging 901, Rayleigh with averaging 902) described hereinand the standard detector (AWGN without averaging 903, Rayleigh withoutaveraging 904). It can be observed that the proposed detector canrobustly detect DVB-T signals even below −15 dB for different channelconditions.

In addition to the peak magnitude, consistency in the periodicity of thepeak can also be used to improve the detector's robustness. According toan example embodiment of the invention, in the cross-correlation basedmethod using s_(d) ^(P) (n) as a reference sequence, the correlationpeak would repeat every 4*N_(SYM) samples in the presence of a DVB-Tsignal. Therefore, the difference in the position of the maximum peak R_(xp,d)(l) on each block of 4*N_(SYM) samples is calculated as shownbelow

D(l)=abs( R _(xp.d)(l)− R _(xp,d)(l−1))l≧2  (14)

If the value of D(l)<D_(threshold) then a DVB-T signal is present. Thevalue of D_(threshold) could be set to a fixed value such as 10(symbols) or may be set by the device based on the operating environmentof the CR device.

Quiet-Period (QP) Sensing

In an example embodiment, in order to maintain quality of service (QoS)requirements of an application, a cognitive radio will not be able tocease its transmission for a continued period of time. Instead, a CRdevice will schedule short quiet periods (QPs) more frequently. In thisexample embodiment, the data smoothing equation is modified as shownbelow.

$\begin{matrix}{{{x_{L}\; (n)} = {\frac{1}{L}{\sum\limits_{l = 0}^{L - 1}{x\left( {n - {l*N_{PPRP}}} \right)}}}}{{n = 0},1,\ldots \mspace{14mu},{N_{QP} - 1}}} & (15)\end{matrix}$

where N_(QP) corresponds to the number of samples that can accommodatedin the given quiet period. N_(QP) could take the values 4*N_(SYM),8*N_(SYM), 12*N_(SYM) . . . , or N_(PPRP), depending on the QP duration.It is assumed that the sample counters are active during non-QPs. Insome situations, a continuous set of samples equal to N_(QP) andcorresponding to the desired range cannot be captured in a given QP. Inthose cases, the samples can be discarded and the process continued withthe next QP.

In another example embodiment of the invention, the implementationcomplexity associated with the cross-correlation can be reduced bymodifying the equation as shown below

$\begin{matrix}{{{R_{{xp},d}^{L}(n)} = {\sum\limits_{m = 0}^{N_{FFT} - 1}{{{sgn}\left( {x_{L}^{*}\left( {n + m} \right)} \right)}{{sgn}\left( {s_{d\;}^{P}(m)} \right)}}}}{{n = 0},1,\ldots \mspace{14mu},N_{PPRP}}} & (16)\end{matrix}$

The product operation in the summation can be implemented as a simplelogic operation and therefore reduces the gate count significantlycompared to a multiplier. FIG. 10 shows the performance of a DVB-T/DVB-Hdetector using cross-correlation as defined in Equation (16).

FIG. 11 shows the process of detecting the presence of a DVB accordingto an example embodiment. The process includes: receiving an RF (radiofrequency) signal in a selected channel 1101; creating signal samplesfrom the received signal 1102; creating averaged samples from the signalsamples, each averaged sample is an average of a predetermined number ofsignal samples that are separated by a minimum pilot pattern repetitionperiod from one to the next signal sample 1103; correlating the averagedsamples with a reference sequence 1104; and comparing a correlationresult with a threshold correlation value 1105. Based on the results ofthe comparison, the presence of a DVB can be determined.

The techniques described in this disclosure can be used in cognitiveradios and other systems that rely on detect-and-avoid techniques forthe detection of DVB-T/H signals or other OFDM signals that includedefined pilot patterns.

The foregoing detailed description has set forth a few of the many formsthat the invention can take. It is intended that the foregoing detaileddescription be understood as an illustration of selected forms that theinvention can take and not as a limitation to the definition of theinvention. It is only the claims, including all equivalents that areintended to define the scope of this invention.

Most preferably, the principles of the invention are implemented as anycombination of hardware, firmware and software. Moreover, the softwareis preferably implemented as an application program tangibly embodied ona program storage unit or computer readable storage medium consisting ofparts, or of certain devices and/or a combination of devices. Theapplication program may be uploaded to, and executed by, a machinecomprising any suitable architecture. Preferably, the machine isimplemented on a computer platform having hardware such as one or morecentral processing units (“CPUs”), a memory, and input/outputinterfaces. The computer platform may also include an operating systemand microinstruction code. The various processes and functions describedherein may be either part of the microinstruction code or part of theapplication program, or any combination thereof, which may be executedby a CPU, whether or not such computer or processor is explicitly shown.In addition, various other peripheral units may be connected to thecomputer platform such as an additional data storage unit and a printingunit.

1. A method for detecting the presence of a DVB (digital videobroadcasting) transmission, comprising: receiving an RF (radiofrequency) signal in a selected channel (1101); creating signal samplesfrom the received signal (1102); creating averaged samples from thesignal samples, each of the averaged samples being an average of apredetermined number of signal samples that are separated by a minimumpilot pattern repetition period from one to the next signal sample(1103); correlating the averaged samples with a reference sequence(1104); and comparing a correlation result with a threshold correlationvalue (1105).
 2. The method of claim 1, further comprising: calculatinga variation in periodicity of correlation peaks from the correlationresults; and comparing the variation with a threshold variation value.3. The method of claim 1, wherein the minimum pilot pattern repetitionperiod depends on the transmission mode and guard interval duration ofthe signal.
 4. The method of claim 3, further comprising determining thetransmission mode by cycling through different transmission modes untilthe DVB signal is detected.
 5. The method of claim 1, wherein thepredetermined number of signal samples depends on a sensing time and/ordesired performance levels.
 6. The method of claim 1, wherein the numberof averaged samples depends on how many samples can be accommodatedduring a quiet period.
 7. The method of claim 1, wherein correlating theaveraged samples with the reference sequence comprises taking logicoperations on the signs of the averaged samples and the referencesequence.
 8. The method of claim 1, wherein the reference sequence isgenerated from pilots and stored in memory.
 9. A method for detectingthe presence of a DVB (digital video broadcasting) transmission,comprising: receiving an RF (radio frequency) signal in a selectedchannel; creating signal samples from the received signal; correlatingthe signal samples with a reference sequence; calculating an averagedcorrelation value by taking an average of correlation resultscorresponding to a predetermined number of signal samples that areseparated by a minimum pilot pattern repetition period from one to thenext signal sample; and comparing the averaged correlation value with athreshold correlation value.
 10. A system for detecting the presence ofa DVB (digital video broadcasting) transmission, comprising: an RF(radio frequency) front-end module (501) for receiving an RF signal; asampling module (502) for creating signal samples from the received RFsignal; a buffer (503) for holding the signal samples; anaccumulating/averaging module (505) for creating averaged samples fromthe signal samples, each of the averaged samples being an average of apredetermined number of signal samples that are separated by a minimumpilot pattern repetition period from one to the next signal sample; amemory module (504) for storing a reference sequence; a correlator (506)for correlating the averaged samples with the reference sequence; and athreshold detection module (507) for comparing a correlation result witha threshold correlation value.
 11. The system of claim 10, wherein thecorrelator (506) is further configured to calculate a variation inperiodicity of correlation peaks from the correlation results, whereinthe threshold detection module (507) is further configured to comparethe variation with a threshold variation value.
 12. The system of claim10, wherein the minimum pilot pattern repetition period depends on thetransmission mode and guard interval duration of the signal.
 13. Thesystem of claim 12, further comprising means for determining thetransmission mode by cycling through different transmission modes untilthe DVB signal is detected.
 14. The system of claim 10, wherein thepredetermined number of signal samples depends on a sensing time and/ordesired performance levels.
 15. The system of claim 10, wherein thenumber of averaged samples depends on how many samples can beaccommodated during a quiet period.